DOI: 10.1007/s10596-019-09898-5
论文题名: A polynomial chaos framework for probabilistic predictions of storm surge events
作者: Sochala P. ; Chen C. ; Dawson C. ; Iskandarani M.
刊名: Computational Geosciences
ISSN: 14200597
出版年: 2020
卷: 24, 期: 1 语种: 英语
英文关键词: Empirical orthogonal functions
; Exceedance probability
; Global sensitivity analysis
; Hurricane Gustav
; Tropical cyclones
; Uncertainty quantification
Scopus关键词: empirical orthogonal function analysis
; Hurricane Gustav 2008
; prediction
; probability
; sensitivity analysis
; storm surge
; tropical cyclone
; uncertainty analysis
英文摘要: We present a polynomial chaos-based framework to quantify the uncertainties in predicting hurricane-induced storm surges. Perturbation strategies are proposed to characterize poorly known time-dependent input parameters, such as tropical cyclone track and wind as well as space-dependent bottom stresses, using a handful of stochastic variables. The input uncertainties are then propagated through an ensemble calculation and a model surrogate is constructed to represent the changes in model output caused by changes in the model input. The statistical analysis is then performed using the model surrogate once its reliability has been established. The procedure is illustrated by simulating the flooding caused by Hurricane Gustav 2008 using the ADvanced CIRCulation model. The hurricane’s track and intensity are perturbed along with the bottom friction coefficients. A sensitivity analysis suggests that the track of the tropical cyclone is the dominant contributor to the peak water level forecast, while uncertainties in wind speed and in the bottom friction coefficient show minor contributions. Exceedance probability maps with different levels are also estimated to identify the most vulnerable areas. © 2019, Springer Nature Switzerland AG. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/159834
Appears in Collections: 气候变化与战略
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作者单位: BRGM, 3 Avenue Claude Guillemin, Orléans, 45060, France; Oden Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, TX 78712, United States; Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL 33149, United States
Recommended Citation:
Sochala P.,Chen C.,Dawson C.,et al. A polynomial chaos framework for probabilistic predictions of storm surge events[J]. Computational Geosciences,2020-01-01,24(1)